Ultrasound imaging provides useful information about the interior characteristics of an object or a subject. In one instance, ultrasound imaging is used to generate both an image of the interior characteristics and estimate flow velocity of flowing structure (e.g., blood cells and tissue motion), and display the image with indicia indicative of the estimated flow velocity superimposed there over. An example ultrasound system uses power Doppler or color flow mapping to identify places of flow, and subsequently uses spectral velocity estimation for determining quantitative measures. For this, ultrasound pulses are emitted continuously in one direction and segments of data are Fourier transformed to yield the velocity distribution from which quantitative velocity measures can be found. An example of this is described in Jensen, “Estimation of Blood Velocities Using Ultrasound: A Signal Processing Approach,” Cambridge University Press, New York, 1996.
However, this approach has several drawbacks. For example, with this approach the velocity is only computed in the axial (or beam) direction and must be angle corrected to yield the velocity magnitude. Most often vessels are parallel to the skin surface and the beam-to-flow angle is close to ninety (90) degrees, making the angle correction unreliable and error prone. The spectral estimates also suffer from spectral broadening artifacts from the segmentation and windowing of the data. A consistent over-estimation of peak and mean velocities are therefore often found. Furthermore, the maximum velocity detectable is limited by the pulse repetition frequency and the employed wavelength, which are fixed. This in combination with the length of the segments used gives the lowest velocity detectable and hence the velocity range, which can be estimated during a single measurement.